NIPS 2017 presentations from the Neuroscience session

Toward GoalDriven Neural Network Models for the Rodent WhiskerTrigeminal System Modelbased Bayesian inference of neural activity and connectivity from alloptical interrogation of a neural circuit Quantifying how much sensory information in a neural code is relevant for behavior Learning to See Physics via Visual Deanimation Shape and Material from Sound Deep Hyperalignment Fast amortized inference of neural activity from calcium imaging data with variational autoencoders Unified representation of tractography and diffusionweighted MRI data using sparse multidimensional arrays Targeting EEG, LFP Synchrony with Neural Nets Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal Neurons